1. Field of the Invention
The present invention generally relates to techniques for the localization of mobile communications terminals like cellular phones. More specifically, the invention concerns a method and a system for increasing the mobile terminals' localization accuracy.
2. Description of the Related Art
Geographic localization of mobile communications terminals like cellular phones, smart phones and similar handheld devices operable with mobile communications networks can be exploited in a variety of services and applications, such as location-sensitive yellow-pages services (e.g., exploiting the known location of a mobile terminal for providing to the user information about restaurants, hotels, etc. in his/her location neighborhood), services offered to communities of users (e.g., friend/family member find services), location-sensitive call billing schemes. Locating mobile communications terminals is also of great importance in case of emergency calls.
Several techniques are known in the art that allow the geographic localization of mobile terminals.
Satellite-based geolocating systems like the GPS (Global Positioning System) are an effective solution for localizing mobile communication terminals. As known in the art, the GPS comprises a “constellation” of satellites that orbit around the earth; each GPS satellite carries a GPS transmitter that transmits GPS signals encoded with information that allows GPS receivers on earth to measure the time of arrival of the received signals relative to an arbitrary point in time: this relative time-of-arrival measurement may then be converted to a “pseudo-range” measure (a measure of the apparent propagation time from the satellite to the GPS receiver, expressed as a distance).
The position (latitude, longitude, height) and the clock offset of a GPS receiver may be accurately estimated based on a sufficient number of available pseudo-range measurements (typically four). Calculating the position (the so-called “GPS fix”) of a GPS receiver involves solving a system of equations where the unknown variables are the GPS receiver geographic coordinates to be determined and the offset between the receiver clock and the GPS system clock.
The GPS performance is rather good in open-sky conditions when the number of received signals is equal to or greater than 5 and all the received signals are in “Line of Sight” (LOS). Depending on the specific signal processing techniques and PVT (Position Velocity Time) algorithms implemented at the GPS receiver, the localization accuracy may in these conditions vary from approximately 2 m to few millimeters.
GPS signals are received at very low power levels, due to the relatively large distances between the satellites and the receivers, and most GPS receivers have great difficulty in receiving GPS signals when they happen to be inside a building, under dense foliage, in urban settings in which tall buildings block much of the sky visibility, and so on.
However, the increase in sensitivity of the GPS receivers has made it possible to use the GPS also not in open-sky, LOS conditions, as it is normally the case of urban and indoor environments, where there is no direct visibility of the satellites and the GPS signal is received after having been diffracted, reflected and strongly attenuated by surrounding obstacles.
GPS techniques in these environments are called High-Sensitivity GPS (HSGPS).
Further improvements in the sensitivity of GPS receivers, as well as the deployment of GNNS (Global Navigation Satellite Systems) complementary to the GPS, like Galileo, are expected to partially overcome the problem of the signals obstruction.
Other known geographic localization techniques of mobile communications terminals rely on information made available by wireless communications networks like cellular networks (PLMNs—Public Land Mobile Networks).
For example, exploiting information adapted to identify the network cell (“cell-ID”) covering (“serving”) the area where a cellular phone is located, possibly in combination with measurements of the power levels of the signals from the neighboring network cells, the location of the cellular phone can be determined. Another technique, that can be exploited in so-called “synchronous” PLMNs (PLMNs in which the different base radio stations of the network modulate the signals synchronously to a common time base unique for the whole network), is based on the E-OTD (Enhanced Observed Time Difference), i.e. on measurements of the propagation delays of the signals transmitted by the PLMN's base radio stations. In non-synchronous PLMNs, mechanisms could in principle be implemented for measuring the phase mismatch between the various signals, however the implementation of these mechanisms is complex and expensive.
A critical aspect of geographic localization techniques in general, and of mobile terminals in particular, is the accuracy by which the geographic location can be established.
For example, the location of a mobile terminal making an emergency call should be determined as precisely as possible, or at least an indication of the degree of uncertainty associated with the determined location of the mobile terminal should be provided, in order to ease the task of finding where the user who placed the call is, and e.g. rescue him/her. The regulatory authorities of some countries have in this respect also set forth minimum accuracy standards.
As far as the GPS is concerned, in open-sky conditions the errors affecting the pseudo-range measurements are estimated by the network of GPS monitoring stations. The statistics of the error is of Gaussian type, and it is characterized by a standard deviation σi. In urban and indoor environments, when the GPS signal received by the GPS receivers is strongly attenuated, the error statistics estimated for the open-sky conditions is however not reliable. Nevertheless, it is possible to characterize the pseudo-range measurement error on the basis of measures of the signal-to-noise ratio. In conditions of strong multipath signal propagation, by using the signal-to-noise ratio measures, it is possible to estimate an average bias error (i.e., an error that causes the statistical distribution not to be centered around a zero value, being instead biased to a different value) affecting the pseudo-range measures, caused by the summation of all the multipath contributions or by a strong reflection, and a respective variance; the noise can thus be described in terms of bias and variance, as if it were a Gaussian variable. The average bias is used to correct the pseudo-range measurement, whereas the variance is exploited for assigning a weight to the individual measurements during the resolution of the system of equations for estimating the position of the GPS receiver. As a result of the calculation of the position, the error in the GPS fix is estimated; under the hypothesis that the error affecting the measurements follows the previously defined statistic, the error affecting the GPS fix is Gaussian, and has a variance that depends on the variance of the individual measurements and on the geometry of the satellite constellation.
There are however situations in which the multipath GPS signal propagation causes the usual error statistics not to be valid; this happens for example when errors derive from relatively high delays in the pseudo-range, that deviate from and are not covered by the statistical model previously defined, due for example to particularly unfavorable environmental conditions, like reflecting walls at a distance of several tens of meters and obstructions to the LOS propagation path, or to peculiar combinations of several multipath signal propagation contributions generated by near obstacles, or thermal-noise induced error in the signaling process performed during the pseudo-range estimation.
When the number of different satellite transmitter signals received by a GPS receiver is higher than the number of unknown variables in the mathematical system of equations to be solved for calculating the GPS fix (typically, when pseudo-range measurements for more than four satellites are available at the GPS receiver), the quality of the calculated GPS fix can be assessed by conducting a statistical test (“integrity test”) on the post-fix residues, which are the differences between the measured pseudo-range values and the expected pseudo-range values calculated on the basis of the obtained GPS fix. The integrity test checks whether the square of the post-fix residues, normalized to the hypothesized variance, is less than a preset threshold, that depends on the degrees of freedom (number of available pseudo-range measurements less the number of unknown variables in the equations system to be solved). If the integrity test is not passed, it is possible to try and recalculate the GPS fix, and applying again the integrity test, after discarding one of the available measurements. By recursively applying this procedure (hereinafter also referred to as the Fault Detection and Exclusion or FDE algorithm), discarding one of the available pseudo-range measurements at a time, outliers, i.e. pseudo-range measurements affected by gross errors, can be detected, and the accuracy of the GPS fix can be increased.
In A. Dalla Torre et al., “Analysis of the Accuracy of Indoor GNSS Measurements and Positioning Solution”, European Navigation Conference (ENC) 2008, Toulouse, Apr. 23-25 2008, the integrity test has been adapted to the conditions typical of urban and indoor environments.
The level of accuracy offered by geographic location techniques based on PLMNs depends on the specific service architecture. For example, in the technique using the cell-ID, the accuracy of the position calculated based on the PLMN's information (“PLMN fix”) depends on the network cells' density; in urban environments, where the cells' density is high, the accuracy of the determined mobile terminal's position is, with a reasonable degree of likelihood, of the order of 100-200 m; the accuracy falls to some kilometers in suburban/extraurban environments, where the cells are less dense. Based on information about the cells' density, it is also possible to associate with each PLMN fix a corresponding estimate of the uncertainty area, usually expressed as a parameter representing the radius of a circular area around the estimated position where the likelihood of actually finding the mobile terminal is approximately equal to 67%; by multiplying this radius for a suitable coefficient, the desired degree of confidence of the calculated PLMN fix can be obtained. In the case of the E-OTD technique, the accuracy of the PLMN fix similarly depends on the cells' density; in urban areas, the accuracy is, with a 67% degree of likelihood, of about 150 m, whereas in rural areas the accuracy falls to 250 m; signals from three network cells need however to be available to implement this technique.
Hybrid techniques for determining the geographic position of mobile communications terminals are also known in the art. Generally, the joint use of different technologies for the geographical localization is called “hybrid location”. In particular, the fix of a mobile communications terminal can be calculated by jointly exploiting the GPS and the PLMN.
In WO 2003/92319, an accurate position estimate for the wireless terminal is initially obtained (e.g., based on a first—accurate—position determination sub-system). For each of one or more transmitters (e.g., base stations) in a second (less accurate) position determination sub-system, an ‘expected’ pseudo-range is computed based on the accurate position estimate for the terminal and the base station location, a ‘measured’ pseudo-range is also obtained, and a pseudo-range residual is then determined based on the expected pseudo-range and the measured pseudo-range. Thereafter, to determine an updated position estimate for the terminal, measured pseudo-ranges are obtained for a sufficient number of transmitters. The updated position estimate is then determined based on the pseudo-ranges for these transmitters.
In WO 2005/003809, the location of a mobile terminal in a given area is determined by including the mobile terminal both in a satellite-based positioning system and in a cellular communications system. The mobile terminal is thus adapted to receive satellite signals from the satellite-based system and to be covered by at least one cell of the cellular communications system. The mobile terminal is configured for determining at least approximately its coordinates, including an altitude coordinate in said area, based on both satellite signals received from the satellite-based system and information related to the cellular communication system. An estimate of the altitude coordinate is derived from the information related to the cellular communications system, whereby satisfactory location performance is ensured also when one or more satellites in the satellite-based system are not visible at the mobile terminal.